Sensors and Responsible Multimodal AI for On-Device Applications
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".
Deadline for manuscript submissions: 30 June 2026 | Viewed by 31
Special Issue Editors
Interests: multimodal AI; responsible AI; on-device AI
Special Issue Information
Dear Colleagues,
Recent advances in low-power processors and compact sensor arrays have moved artificial intelligence from distant cloud servers to everyday devices such as smartphones, wearables, and autonomous robots. These edge systems now combine camera, audio, inertial, and biomedical signals to understand complex real-world contexts in real time. While this shift unlocks faster responses and stronger privacy, it also raises novel challenges in fairness, transparency, and energy use. This Special Issue invites research that unites sensor innovation with lightweight, multimodal machine learning under clear principles of responsible AI. We welcome studies on algorithms, hardware–software co-design, datasets, and case-study deployments that demonstrate how trustworthy intelligence can run locally, conserve resources, and respect user data.
Dr. Taehoon Kim
Dr. YoungJoon Yoo
Guest Editors
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Keywords
- on-device AI
- multimodal sensor fusion
- TinyML and model compression
- privacy-preserving learning
- federated or split learning
- energy-efficient inference
- fairness and accountability in AI
- wearable and IoT sensing
- edge hardware acceleration
- real-world benchmarking
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